Week 7 Discussion: Hypothesis Testing

Week 7 Discussion: Hypothesis Testing

Hypothesis testing is a statistical approach whereby the researcher or data analysist tests the assumption concerning the population parameter. In the hypothesis testing process, different data analysts may use disparate approaches. The methodology applied by data analysts may depend on the dataset used. In other words, the methodology used usually depends on the data that has been collected as well as the reason for data analysis. In most cases, hypothesis testing is applied in the evaluation of the plausibility or credibility of the hypothesis by the use of sample data. There is null and alternative hypothesis (Kunisky, Wein, & Bandeira, 2019). Null hypothesis is stated in the negative statement while alternative hypothesis is stated in a positive statement. In other words, null hypothesis is a hypothesis of equality between the population parameters. For instance, a null hypothesis may state that the population mean value is zero. Since the alternative hypothesis is the opposite of the null hypothesis, it can be stated that the population mean return is equal to zero (List, Shaikh, & Xu, 2019). The two sides are mutually exclusive and at a given instance, only one can be true. In other words, one of the two hypotheses will be true at the end of the study.

A hypothesis test study that would help my work in some way is: The effect of body mass index on blood pressure. In this hypothesis test study, there will be the determination of whether there is significant effects of body mass index on the blood pressure. The two variables that will be tested are “Body Mass Index” and “Blood Pressure” In other words, the dependent variable is Blood Pressure while the independent variable is Body Mass Index. Alternatively, the variable that will be tested is Body Mass Index. From the two variables, the hypothesis can be stated as follows:

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Null Hypothesis (Ho): There is no significant effect of body mass index on the blood

                                          Pressure

Alternative Hypothesis (H1):  There is no significant effect of body mass index on the

                                                     blood pressure

The outcome of the study is expected to show that there is significant impacts of body mass index on high blood pressure. In other words, it is expected that there is significant effective of the independent variable on the dependent variable. Before undertaking the hypothesis test, there is need to collect and arrange data to ensure effective outcomes. A student t-test can be applied in the hypothesis testing to ensure effective outcomes. In the above cases, when the null hypothesis is rejected, the alternative hypothesis is used to make a conclusion and when the null hypothesis is accepted, it is used to make meaningful conclusion.

If the null hypothesis is rejected in the above case, then the expected outcome will stand. In other words, there will be a conclusion that there is a significant effect of body mass index on the blood pressure. On the other hand, accepting null hypothesis means that the expected outcome will not stand. Therefore, rejecting the null hypothesis will not change my conclusion or actions in some ways while accepting the null hypothesis may change my conclusion or action in different ways.

References

Kunisky, D., Wein, A. S., & Bandeira, A. S. (2019). Notes on computational hardness of hypothesis testing: Predictions using the low-degree likelihood ratio. arXiv preprint arXiv:1907.11636. https://arxiv.org/abs/1907.11636

List, J. A., Shaikh, A. M., & Xu, Y. (2019). Multiple hypothesis testing in experimental economics. Experimental Economics, 22(4), 773-793. https://doi/10.1007/s10683-018-09597-5